Background: Pancreas cancer patients have a dismal prognosis, with the cumulative 5-year survival of 7%. Most patients present with locally advanced (LAPC) or borderline resectable (BRPC) pancreatic cancer. The overall survival rates in the patients undergoing margin-negative resection after chemoradiation therapies are 2-3 times of the unresected group. The superior outcome of surgery calls for novel local treatment strategies aiming at downstaging patients and improving resection rate. Targeted therapy such as stereotactic body radiation therapy (SBRT) with simultaneous integrated boost (SIB) to tumor infiltrating blood vessels has the potential to sterilize cancerous tissue around the vessels that limit surgery. However, the SIB treatment is not commonly applied due to challenges in managing internal organ motion, visualization and segmentation of boost volumes, and tracking the tumor response to the therapy with current CT based planning and response assessment. Magnetic resonance imaging (MRI) is intrinsically superior to CT in soft tissue contrast, but until recently, few sequences were available to address the specific needs in pancreas radiotherapy including the need to resolve motion and differentiate tumor infiltrated vessels. We pioneered a 3D k-space resorting based four-dimensional MRI (4D- MRI) technique for the abdomen. Despite its high resolution, the current 4D-MRI images have insufficient vessel contrast for segmenting and targeting. Goals: The first goal of this study is to optimize the 4D-MRI technique so it generates a sufficiently high blood vessel contrast for SBRT-SIB target localization. The second goal is to use this novel 4D-MRI with vessel highlight to identify imaging makers that predict tumor resectability after chemoradiation therapy intervention. Methods: We will optimize the novel sequence by incorporating a new slab-selective function which highlights tumor encasing blood vessels and quantify the enhancement of contrast-to-noise (CNR) ratio as well as morphological changes for the vessels within the pancreatic tumor. A flow phantom and healthy volunteers will be used to optimize 4D-MRI parameters such as the number of radial lines, resolution and slab-selective volume. The CNR will be correlated to flow rates in the phantom. To validate the method, we will also recruit 30 patients diagnosed with LAPC or BRPC and perform pre- and post- chemoradiation 4D-MRI studies. The changes of the vessel CNR, geometry and morphology will be correlated to standard clinical outcomes. Impact: Success of this study will provide a non-invasive imaging method capable of localizing tumor involving blood vessels while overcoming respiratory motion blur. The information will be available to guide targeted radiation dose escalation to the boost volume defined by the involved vessels, which initially preclude resection. Therefore, the project answers an unmet need in current pancreatic cancer management since more than 85% of the patients have non-resectable cancer due to vessel involvement.